Cited by Nano-sized MIL-101(Cr) MOF for CO2 separation: Crystal downsizing effects on adsorption and mixed matrix membranes

Artificial intelligence‐driven sustainability: Enhancing carbon capture for sustainable development goals– A review DOI

Sivasubramanian Manikandan,

R Kaviya,

Dhamodharan Hemnath Shreeharan

и другие.

Sustainable Development, Год журнала: 2024, Номер unknown

Опубликована: Окт. 6, 2024

Abstract Artificial intelligence (AI) and environmental points are equally important components within the response to local weather change. Therefore, based on efforts of reducing carbon emissions more efficiently effectively, this study tries focus AI integration with capture technology. The urgency tackling climate change means we need advanced capture, is an area where can make a huge impact in how these technologies operated managed. It will minimize manufacturing improve both resource efficiency as well our planet's footprint by turning waste into something value again. could be leveraged analyze data sets from plants, searching for optimal system settings efficient ways identifying patterns available information at larger scale than currently possible. In addition, incorporated sensors monitoring mechanisms supply chain identify any operational failure reception itself allowing timely action protect those areas. also helps generative design materials, which allows researchers explore new types carbon‐absorbing material, including metal–organic frameworks polymeric materials that industrial CO 2 , such moisture. it increases accuracy reservoir simulations controls injection systems storage or enhanced oil recovery. Through applying algorithms geology, production performance real‐time would like facilitate optimization processes while assuring maximum efficiency. integrates renewable‐based employed AI‐driven smart grid methods.

Язык: Английский

Процитировано

Mixed matrix membrane formation with porous metal–organic nanomaterials for CO2 capture and separation: A critical review DOI